Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates

James Wolter

No 761, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: Abstract We propose a hazard model where dependence between events is achieved by assuming dependence between covariates. This model allows for correlated variables specific to observations as well as macro variables which all observations share. This setup better fits many economic and financial applications where events are not independent. Nonparametric estimation of the hazard function is then studied. Kernel estimators proposed in Nielsen and Linton (1995, Annals of Statistics) and Linton, Nielsen and Van de Geer (2003, Annalsof Statistics) are shown to have similar asymptotic properties compared with the i.i.d.case. Mixing conditions ensure the asymptotic results follow. These results depend on adjustments to bandwidth conditions. Simulations are conducted which verify the impact of dependenceon estimators. Bandwidth selection accounting for dependence is shown to improve performance. In an empirical application, trade intensity in high-frequency financial data is estimated.

Keywords: Hazard estimation; Correlated events; Dependent covariates; Common covariates; Kernel estimation. (search for similar items in EconPapers)
JEL-codes: C13 C14 C51 (search for similar items in EconPapers)
Date: 2015-10-05
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ora.ox.ac.uk/objects/uuid:cc5a232f-7d6d-4b21-b071-f937ef6d7ee1 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oxf:wpaper:761

Access Statistics for this paper

More papers in Economics Series Working Papers from University of Oxford, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Anne Pouliquen ( this e-mail address is bad, please contact ).